Title :
Fast solution technique for large-scale unit commitment problem using genetic algorithm
Author :
Senjyu, T. ; Yamashiro, H. ; Shimabukuro, K. ; Uezato, K. ; Funabashi, T.
Author_Institution :
Fac. of Eng., Univ. of the Ryukyus, Okinawa, Japan
Abstract :
An approach for a large-scale unit commitment problem is presented. The unit commitment (UC) problem plays a major role in power systems, because the improvement of commitment schedules results in the reduction of operating costs. However, the unit commitment problem is one of the most difficult optimisation problems in power systems, because this problem has many constraints. Moreover, search space is vast. To overcome these problems, a new genetic operator based on unit characteristic classification and unit integration technique are proposed. The proposed algorithm was tested on a reported UC problem. From simulation results, better solutions are obtained in comparison with previously reported results. Numerical results for systems up to 100 units are compared to previously reported results.
Keywords :
genetic algorithms; power generation scheduling; arge-scale unit commitment problem; commitment schedules; fast solution technique; genetic algorithm; genetic operator; operating costs reduction; search space; unit characteristic classification; unit integration technique;
Journal_Title :
Generation, Transmission and Distribution, IEE Proceedings-
DOI :
10.1049/ip-gtd:20030939